Return to search

Time-varying impacts of green credit on carbon productivity in China: New evidence from a non-parametric panel data model

Yes / In the context of global climate change threatening human survival, and in a post-pandemic era that advocates for a global green and low-carbon economic recovery, conducting an in-depth analysis to assess whether green f inance can effectively support low-carbon economic development from a dynamic perspective is crucial. Unlike existing research, which focuses solely on the average effects of green credit (GC) on carbon productivity (CP), we introduce a non-parametric panel data model to investigate GC’s impact on CP across 30 provinces in China from 2003 to 2021, verifying a significant time-varying effect. Specifically, during the first phase (2003–2008), GC negatively impacted CP. In the second phase (2009–2014), this negative influence gradually diminished and transformed into a positive effect. In the third phase (2015–2021), GC continued to positively influence CP, although this effect became insignificant during the pandemic. Further subgroup analysis reveals that in the regions with low environmental regulations, GC did not significantly boost CP throughout the sample period. In contrast, in the regions with high environmental regulations, GC’s positive effect persisted in the mid to late stages of the sample period. Additionally, compared to the regions with low levels of marketization, the impact of GC on CP was more pronounced in highly marketized regions. This indicates that the promoting effect of GC on CP depends on strong support from environmental regulations and well-functioning market mechanisms. By adopting a non-parametric approach, this study reveals variations in the impact of GC on CP across different stages and under the influence of the pandemic shock, offering new insights into the relationship between GC and China’s CP. / The full-text of this article will be released for public view at the end of the publisher embargo on 15 May 2025.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19924
Date16 July 2024
CreatorsHou, P., Luo, S., Liu, S., Tan, Yong, Roubaud, D.
Source SetsBradford Scholars
LanguageEnglish, English
Detected LanguageEnglish
TypeArticle, Accepted manuscript
Rights© 2024 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/), CC-BY-NC-ND

Page generated in 0.0019 seconds